X-TRACK based on xLSTM achieves SOTA.
“Compared to state-of-the-art baselines, X-TRACK achieves performance improvement by 79% at the 1-second prediction and 20% at the 5-second prediction in the case of highD”
Again xLSTM excels.
X-TRACK based on xLSTM achieves SOTA.
“Compared to state-of-the-art baselines, X-TRACK achieves performance improvement by 79% at the 1-second prediction and 20% at the 5-second prediction in the case of highD”
Again xLSTM excels.
AES is a major power provider for Big Tech companies building out data centers.
Yes: while these data centers drive up your electricity costs, wealthy financiers are going to make a killing.
📷️: Al Drago/Andrea Verdelli, Bloomberg
arxiv.org/abs/2506.09650
arxiv.org/abs/2506.09650
Paper: arxiv.org/abs/2505.23719
Code: github.com/NX-AI/tirex
Paper: arxiv.org/abs/2505.23719
Code: github.com/NX-AI/tirex
➡️ Outperforms models by Amazon, Google, Datadog, Salesforce, Alibaba
➡️ industrial applications
➡️ limited data
➡️ embedded AI and edge devices
➡️ Europe is leading
Code: lnkd.in/eHXb-XwZ
Paper: lnkd.in/e8e7xnri
shorturl.at/jcQeq
➡️ Outperforms models by Amazon, Google, Datadog, Salesforce, Alibaba
➡️ industrial applications
➡️ limited data
➡️ embedded AI and edge devices
➡️ Europe is leading
Code: lnkd.in/eHXb-XwZ
Paper: lnkd.in/e8e7xnri
shorturl.at/jcQeq
Paper: arxiv.org/abs/2505.23719
Code: github.com/NX-AI/tirex
Paper: arxiv.org/abs/2505.23719
Code: github.com/NX-AI/tirex
https://www.ft.com/content/9c652f09-cfca-4078-9e2b-5fdacd772a75
arxiv.org/abs/2505.18012
arxiv.org/abs/2505.18012
arxiv.org/abs/2501.06146
arxiv.org/abs/2501.06146
youtu.be/CpuN-yM1sZU?...
youtu.be/CpuN-yM1sZU?...
arxiv.org/abs/2504.07965
arxiv.org/abs/2504.07965
arxiv.org/abs/2401.17173
arxiv.org/abs/2401.17173
In AI this would be called "Sector Accounting is All You Need".
In AI this would be called "Sector Accounting is All You Need".